Heart disease is the leading cause of death in the United States. A heart attack, also known as an acute myocardial infarction (AMI), typically results from a blood clot or “thrombus” that obstructs blood flow in one or more coronary arteries. AMI is a common and life-threatening complication of coronary artery disease. Coronary ischemia is caused by an insufficiency of oxygen to the heart muscle. Ischemia is typically provoked by physical activity or other causes of increased heart rate when one or more of the coronary arteries is narrowed by atherosclerosis. AMI, which is typically the result of a completely blocked coronary artery, is the most extreme form of ischemia. Patients will often (but not always) become aware of chest discomfort, known as “angina”, when the heart muscle is experiencing ischemia. Those with coronary atherosclerosis are at higher risk for AMI if the plaque becomes further obstructed by thrombus.
There are a number of portable monitors that attempt to detect AMI. Monitors that include wearable sensors (e.g. a medical-vest with electrodes) may be somewhat inconvenient for patients. Chronically implanted sensors provide the possibility for continuous monitoring without many of the inconveniences associated with wearable monitors. One type of implantable monitor includes an electrode chronically implanted within the heart. An intracardiac electrode may provide a strong signal at the cost of requiring intracardiac implantation. Another type of implantable monitor can rely upon subcutaneous electrodes, which are less invasive, but receive smaller amplitude signals compared to intracardiac electrodes.
Furthermore, subcutaneous electrodes require lead structures to connect them to the monitoring device. If the lead is also subcutaneous, it is generally desirable to keep it as short as possible. Shorter leads provide a more limited view of the torso's electrical field, which may in turn compromise the ability of a monitoring device to detect certain types of cardiac events. It would be desirable to have a subcutaneous electrode and lead system with relatively short leads that can diagnose a variety of cardiac conditions, including ischemia associated with significant occlusions of any of the three major coronary arteries, the left anterior descending artery, the left circumflex artery and the right coronary artery.
U.S. patent application Ser. No. 11/889,752, entitled “SYSTEM AND METHODS FOR DETECTING ISCHEMIA WITH A LIMITED EXTRACARDIAC LEAD SET”, filed 16 Aug. 2007, (“Limited Lead Set Application”) assigned to the assignee of the present application, discloses (inter alia) a two lead system with one lead extending from the anterior precordial region to the lower left side and the other extending from the anterior/superior region to the right of the first lead to the inferior right side. The '752 application describes a number of prior devices/techniques for detecting ischemia based on extracardiac electrical recordings.
Heart rate corrected QT and JT intervals, known as QTc and JTc respectively, have been widely used to assess cardiac repolarization, which is affected by many different types of pathologies, including acute ischemia. The QT and JT intervals are the times between the end of the T wave and the onset of the Q wave and J point, respectively. QT interval analysis on ambulatory electrocardiogram recordings: a selective beat averaging approach. With regard to ambulatory recordings, a number of beats may be averaged together to derive a representative beat whose QT interval is measured. (E.g. see Badilini et al., “QT interval analysis on ambulatory electrocardiogram recordings: a selective beat averaging approach,” Med Biol Eng Comput. 1999 January; 37(1):71-9.) Signal averaging requires the alignment of different beats and generally also requires the removal of beats that don't fit a template; these steps are somewhat computationally expensive.
Sun et al. (“Characteristic wave detection in ECG signal using morphological transform”; BMC Cardiovasc Disord. 2005; 5: 28) describe a multi-scale derivative method for locating QRS (and P and T) wave fiducial points. “Long distance” derivatives/differences (e.g. f(x+n)−f(x), where n>1) are taken both before and after each candidate onset point and the difference between these derivatives is calculated to form a type of second derivative/difference which the authors term a “multiscale morphological derivative transform.” QRS onset or other fiducial points are defined as the maxima or minima of this “transform.” Kemmelings et. al. describe a QRS onset/offset detection scheme that involves summing the absolute value of the first derivative (difference) and then taking a “long distance” derivative of this summed signal, to find where it abruptly changes (over a large scale). (“Automatic QRS onset and offset detection for body surface Q RS integral mapping of ventricular tachycardia.”; IEEE Trans Biomed Eng. 1994; 41:830-836). Hayn et al., Automated QT Interval Measurement from Multilead ECG Signals. Comp. Card. 33:3814, 2006 describe a method for detecting Q wave onset by iteratively selecting possible QRS onset points by finding, for each step in the iteration, the point characterized by the “most distinct change in the range curve” around the point. T wave offsets were also found by this method, as well as by fitting a Guassian curve to the T wave and defining the offset with respect to the standard deviation of the curve.
Zong et al. (A robust open-source algorithm to detect onset and duration of QRS complexes, Computers in Cardiology, 2003, Issue, 21-24 Sep. 2003, Page(s): 737-740) describe a method for detecting QRS onset and offset points by using a function that corresponds to the “distance” by the signal; the function has the form (D2+(Δs/Δt)2)0.5, where D is a constant and Δs is the difference between successive samples of an ECG signal and Δt is the time between samples (i.e. the inverse of the sampling frequency). This function is essentially a discrete version of the calculus formula for distance along a curve, which is based on the first derivative of the curve.
Arini et al. (Evolution of T Wave Width During Severe Ischemia Generated by Percutaneous Transluminal Coronary Angioplasty, Computers in Cardiology 2006; 33:713-716), describe methods for assessing the presence/severity of ischemia based on T wave width, which in turn requires a computation of T wave onset and offset times.
In U.S. Pat. No. 6,397,100 to Stadler and Shannon, ST segment values are low pass filtered to ensure that very rapid changes, which may be caused by axis shifts, are not considered to be ST shifts caused by ischemia. Two different low pass filters are applied, resulting in two different filtered signals. One filtered signal is representative of very slow ST baseline drift. The other filtered signal is representative of the true ST level excluding high frequency axis shift. ST segment deviation indicative of ischemia is equal to the difference between the filtered signals.
In healthy persons, increases in heart rate generally decrease QRS amplitudes (see Miller et al, Circulation; 62(3):632-645, 1980) and decrease QRS duration (Cantor A et al., “QRS prolongation measured by a new computerized method: a sensitive marker for detecting exercise-induced ischemia”, Cardiology. 1997 September-October; 88(5):446-52). (These changes are consistent with an exercise induced reduction in action potential amplitude and increase in cell resting potential.) As a result of these changes, the high frequency content of the QRS in normals tends to increase with increasing heart rate. Some data indicates the high frequency QRS content of ischemic patients decreases with increases in heart rate and also decreases during balloon angioplasty/acute ischemia. (Pettersson et al., “Changes in high-frequency QRS components are more sensitive than ST-segment deviation for detecting acute coronary artery occlusion.” J Am Coll Cardiol. 2000 Nov. 15; 36(6): 1827-34.)
Consequently, the high frequency content of the QRS has been proposed as a marker of ischemia. To derive a measure of the high frequency QRS spectral content, Pettersson et al. disclose the steps of isolating QRS complexes, signal averaging them, and then passing them through a filter with a passband of 150-250 Hz. The root mean square value of the resulting filtered QRS is then obtained. Another method of analyzing high frequency QRS content involves a search for portions within the envelope of the filtered QRS signal that have a smaller amplitude in comparison with neighboring portions of the filtered QRS, i.e. these “reduced amplitude zones” constitute a trough in between peaks of the filtered QRS.
Pueyo et al. (“High-Frequency Signature of the QRS Complex across Ischemia Quantified by QRS Slopes”, Computers in Cardiology 2005; 32:659-662) describe a method for examining the R and S wave slopes and amplitudes, associated with the standard 12 lead electrocardiogram leads, during balloon occlusions. The maximum local upslope and downslope points are determined and lines are fitted in a least squares sense to the 15 ms windows surrounding these points. The slopes of these lines are the ischemia markers.
Lander et al. (“Abnormal intra-QRS potentials associated with percutaneous transluminal coronary angiography-induced transient myocardial ischemia”; J. Electrocardiol. 2006 July; 39(3):282-9) describe a method for determining the presence of slurs or notches in the QRS complex; the presence of such abnormal intra-QRS potentials is indicative of ischemia (or other abnormalities affecting conduction). The QRS is transformed into the frequency domain and then effectively separated into a deterministic/smooth portion and a residual/unpredictable portion. The deterministic/smooth portion is transformed back into the time domain and subtracted from the original QRS, leaving a time domain residual QRS representative of abnormal notches, slurs or the like.
In U.S. Pat. No. 5,046,504, Albert et al. disclose a method for performing a frequency analysis (e.g. by FFT) of overlapping portions of the QRS complex, thereby deriving a “spectro-temporal map” that shows how the frequency content of the QRS changes over the course of the QRS. The '504 patent describes various methods for displaying spectro-temporal maps and information extracted therefrom. The '504 patent also describes methods for determining the presence of “late-potentials” from the spectro-temporal maps and information extracted therefrom.
Despite all of the foregoing work that has been done, there is still a need for an effective subcutaneous or surface based system for monitoring ischemia.